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Abstract.The main task of this paper is to examine a short term trend trading strategy in futures market based on chart pattern recognition, time series and computational analysis. Specifi cations of historical data for technical analysis and equations for futures profi tability calculations together with position size measurement are also discussed in the paper. A contribution of this paper lies in a novel chart pattern related to fractal formation and chaos theory and its application to short term up-trend trading. Trading strategy was tested with historical data of the most active futures contracts. The results have given signifi cantly better and stable returns compared to the change of market benchmark (CRB index). The results of experimental research related to the size of trading portfolio and trade execution slippage are also discussed in the paper. The proposed strategy can be attractive for futures market participants and be applied as a decision support tool in technical analysis.

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The article presents Enterprise Model (EM) generation process from SysML models of four types (Use Case, Activity, Block Definition and Requirements) as well as Knowledge Based MDA (Model-Driven Architecture) tool's prototype which is implementing the defined algorithms. Defined SysML models parsing algorithms use the recursive data processing approach due to complex UML models structure. The algorithms description is presented as Activity diagrams and explained in tables, where are depicted basics steps and actors as well as the output results. Knowledge Based MDA tool's prototype currently is capable of processing Use Case and Activity models. Proposed prototype is implemented using three layers (GUI, Logic and Data) architecture. The detailed architecture is presented and described in this article using class diagrams. The prototype is implemented using .Net framework and C# programming language.